Ethnomedicinal Plants Used in the Healthcare Systems of Tribes of Dantewada, Chhattisgarh India

The tribal people depend on forests for their livelihood and most of the rural people still depend on traditional medicine as a primary healthcare source. The paper highlights the rich plant resources and the vast wealth of ethnobotanical information available with the various tribes of the region. In this paper, some new and less known ethno medicinal uses of 104 plants of tribes of Dantewada, Dakshin Bastar C.G. in different ailments have been reported. The main objective of present work is to give the information and documentation of medicinal plant used by tribal of the study sites. The ethnomedicinal information was gathered from interviews with living elders belonging to Madiya, Muriya, Gond and Bhatra tribes of the study area. The present work on ethnomedicinal plants, used in the healthcare systems of tribes in 15 villages, was carried out from Geedam block of Dantewada, Dakshin Bastar C.G.

A New Approach for Identifying Potentially Effective Indigenous Plants Consumed by Chenchu Tribes and Their Nutritional Composition-India

Traditional knowledge of plants and their properties always has been transmitted from generation to generation through the natural path of everyday life. Food habits of the indigenous population across the globe are very abnormal when compared to that of civilized people. The forest related tribal scientific studies of edible wild plants are extremely constructive to know the nutritional values of the forest indigenous foods and help to eliminate the malnutrition problems in vulnerable group. The existing study was undertaken with an intention and documented 34 exceptional plant species belonging to 15 families with their medicinal values, taxonomical names and nutritional profile. Among the 34 indigenous plant foods, the frequently available and consumed plant foods by particularly vulnerable tribal group Chenchu tribes were selected for nutritional investigation including proximate composition, mineral and vitamin analysis. Results show that the nutritional values of the edible indigenous plant foods are prominent compared to frequently consumed foods available in market. The present study observed that the conventional and nutritional information on wild plant foods is on sharp decline. Unless efforts are made to educate the present generations about the importance of these foods, which may be lost in near future. These studies could contribute significantly to Government policies to improve food security and helps to progress health and nutritional status in marginally deprived tribal communities in India, and in the enhancement of wild vegetable status, whose potential as sources of nutrition is currently undervalued.

Emergence of Multidrug-Resistant Proteus mirabilis Harboring both blaNDM-1 and cfr genes

Proteus mirabilis is abundant in soil and water,and although it is part of the normal human intestinal flora(along with Klebsiella species and Escherichia coli),it is known to cause serious infections in humans,with a fatality rate of 20%-50%[1].Proteus mirabilis is intrinsically resistant to tetracycline,tigecycline,and colistin.The widespread and irregular use of antimicrobial agents,P.mirabilis antimicrobial resistance has mirabilis.They acquire antimicrobial resistance(AMR)by capturing plasmids,transposons,or other mobile elements harboring antimicrobial resistance genes.This mechanism allows the rapid selection and transmission of numerous AMR genes in clinical,veterinary,food production,transportation,and environmental settings.

Optical redox imaging of ANT1-de-cient muscles

Adenine nucleotide translocator(ANT)is a mitochondrial protein involved in the exchange of ADP and ATP across the mitochondrial inner membrane.It plays a crucial role in cellular energy metabolism by facilitating the transport of ATP synthesized within the mitochondria to the cytoplasm.The isoform ANT1 predominately expresses in cardiac and skeletal muscles.Mutations or dysregulation in ANT1 have been implicated in various mitochondrial disorders and neuromuscular diseases.We aimed to examine whether ANT1 deletion may affect mitochondrial redox state in our established ANT1-de-cient mice.Hearts and quadriceps resected from age-matched wild type(WT)and ANT1-de-cient mice were snap-frozen in liquid nitrogen.The Chance redox scanner was utilized to perform 3D optical redox imaging.Each sample underwent scanning across 3–5 sections.Global averaging analysis showed no signi-cant differences in the redox indices(NADH,flavin adenine dinucleotide containing-flavoproteins Fp,and the redox ratio Fp/(NADH+Fp)between WT and ANT1-de-cient groups.However,quadriceps had higher Fp than hearts in both groups(p¼0:0004 and 0.01,respectively).Furthermore,the quadriceps were also more oxidized(a higher redox ratio)than hearts in WT group(p¼0:004).NADH levels were similar in all cases.Our data suggest that under non-stressful physical condition,the ANT1-de-cient muscle cells were in the same mitochondrial state as WT ones and that the signi-cant difference in the mitochondrial redox state between quadriceps and hearts found in WT might be diminished in ANT1-de-cient ones.Redox imaging of muscles under physical stress can be conducted in future.

An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect.The contemporary methods of steganography are at best a compromise between these two.In this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic embedding.The approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret data.This approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale images.The ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual quality.Pheromone evaporation is introduced through iterations to avoid stagnation in solution refinement.The levels of pheromone are modified to reinforce successful pixel choices.Experimental results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of 0.98.The approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.

MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

Micro-Arthropods in the Surroundings of Nests of Messor arenarius Ants in the Negev Desert in Israel

The present research investigated a segment of the micro-arthropod populations residing within nests of Messor arenarius ants in the Negev Desert of Israel. The total frequencies of micro-arthropods in the chaff of those ants’ nests were found to be higher than in the surrounding soil of the same nests. Acari (mites) were observed to be more abundant during the spring season, whereas their presence decreased during the summer months. Springtails (Collembola) were found to follow the Acari pattern, commonly found within the nests of those ants during spring but were absent during summer. Psocoptera order inhabiting soil habitats were infrequently encountered during spring, but their prevalence increased significantly during summer, particularly within the chaff of the ants’ nests, suggesting that chaff is their primary food source in the Negev Desert. Our research suggests that shifts in seasonality have important consequences on the distribution of soil invertebrate communities with implications on nutrient cycling.

Planning of a Single Flow Channel in Valve Blocks Based on Additive Manufacturing and the Ant Colony Algorithm

As electro-hydrostatic actuator(EHA)technology advances towards lightweight and integration,the demand for enhanced internal flow pathways in hydraulic valve blocks intensifies.However,owing to the constraints imposed by traditional manufacturing processes,conventional hydraulic integrated valve blocks fail to satisfy the demands of a more compact channel layout and lower energy dissipation.Notably,the subjectivity in the arrangement of internal passages results in a time-consuming and labor-intensive process.This study employed additive manufacturing technology and the ant colony algorithm and B-spline curves for the meticulous design of internal passages within an aviation EHA valve block.The layout environment for the valve block passages was established,and path optimization was achieved using the ant colony algorithm,complemented by smoothing using B-spline curves.Three-dimensional modeling was performed using SolidWorks software,revealing a 10.03%reduction in volume for the optimized passages compared with the original passages.Computational fluid dynamics(CFD)simulations were performed using Fluent software,demonstrating that the algorithmically optimized passages effectively prevented the occurrence of vortices at right-angled locations,exhibited superior flow characteristics,and concurrently reduced pressure losses by 34.09%-36.36%.The small discrepancy between the experimental and simulation results validated the efficacy of the ant colony algorithm and B-spline curves in optimizing the passage design,offering a viable solution for channel design in additive manufacturing.

基于Ant Design Pro的物流系统前端开发与用户体验优化研究

本文探讨了Ant Design Pro在物流系统开发中的应用,特别是其对用户体验和数据可视化的影响。通过采用案例研究方法,分析Ant Design Pro在构建企业级物流系统中的应用。研究发现,Ant Design Pro的一致性设计和丰富的组件库显著提升了开发效率和用户交互体验。此外,其数据可视化组件有效支持了复杂物流数据的呈现和分析。然而,其在性能优化和定制化需求方面面临着挑战。最终,本文提出了一系列基于Ant Design Pro的物流系统开发最佳实践,并对其潜在的改进方向进行了讨论。研究结果为物流行业的信息系统开发提供了实用的指导,并为Ant Design Pro社区贡献了宝贵的实践经验。

Multi-Label Feature Selection Based on Improved Ant Colony Optimization Algorithm with Dynamic Redundancy and Label Dependence

The world produces vast quantities of high-dimensional multi-semantic data.However,extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging.Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features.The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection,because of its simplicity,efficiency,and similarity to reinforcement learning.Nevertheless,existing methods do not consider crucial correlation information,such as dynamic redundancy and label correlation.To tackle these concerns,the paper proposes a multi-label feature selection technique based on ant colony optimization algorithm(MFACO),focusing on dynamic redundancy and label correlation.Initially,the dynamic redundancy is assessed between the selected feature subset and potential features.Meanwhile,the ant colony optimization algorithm extracts label correlation from the label set,which is then combined into the heuristic factor as label weights.Experimental results demonstrate that our proposed strategies can effectively enhance the optimal search ability of ant colony,outperforming the other algorithms involved in the paper.

Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance

Wireless Sensor Networks(WSNs)are a collection of sensor nodes distributed in space and connected through wireless communication.The sensor nodes gather and store data about the real world around them.However,the nodes that are dependent on batteries will ultimately suffer an energy loss with time,which affects the lifetime of the network.This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability.The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization(MFOA-EACO),where the Mayfly Optimization Algorithm(MFOA)is used to select the best cluster head(CH)from a set of nodes,and the Enhanced Ant Colony Optimization(EACO)technique is used to determine an optimal route between the cluster head and base station.The performance evaluation of our suggested hybrid approach is based on many parameters,including the number of active and dead nodes,node degree,distance,and energy usage.Our objective is to integrate MFOA-EACO to enhance energy efficiency and extend the network life of the WSN in the future.The proposed method outcomes proved to be better than traditional approaches such as Hybrid Squirrel-Flying Fox Optimization Algorithm(HSFLBOA),Hybrid Social Reindeer Optimization and Differential Evolution-Firefly Algorithm(HSRODE-FFA),Social Spider Distance Sensitive-Iterative Antlion Butterfly Cockroach Algorithm(SADSS-IABCA),and Energy Efficient Clustering Hierarchy Strategy-Improved Social Spider Algorithm Differential Evolution(EECHS-ISSADE).

Tower crane path planning based on improved ant colony algorithm

In order to solve the problem of path planning of tower cranes,an improved ant colony algorithm was proposed.Firstly,the tower crane was simplified into a three-degree-of-freedom mechanical arm,and the D-H motion model was established to solve the forward and inverse kinematic equations.Secondly,the traditional ant colony algorithm was improved.The heuristic function was improved by introducing the distance between the optional nodes and the target point into the function.Then the transition probability was improved by introducing the security factor of surrounding points into the transition probability.In addition,the local path chunking strategy was used to optimize the local multi-inflection path and reduce the local redundant inflection points.Finally,according to the position of the hook,the kinematic inversion of the tower crane was carried out,and the variables of each joint were obtained.More specifically,compared with the traditional ant colony algorithm,the simulation results showed that improved ant colony algorithm converged faster,shortened the optimal path length,and optimized the path quality in the simple and complex environment.

A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

An Effective Optimization Algorithm for Ant Colony Vehicular Congestion Management

Adaptability and dynamicity are special properties of social insects derived from the decentralized behavior of the insects. Authors have come up with designs for software solution that can regulate traffic congestion in a network transportation environment. The effectiveness of various researches on traffic management has been verified through appropriate metrics. Most of the traffic management systems are centered on using sensors, visual monitoring and neural networks to check for available parking space with the aim of informing drivers beforehand to prevent traffic congestion. There has been limited research on solving ongoing traffic congestion in congestion prone areas like car park with any of the common methods mentioned. This study focus however is on a motor park, as a highly congested area when it comes to traffic. The car park has two entrance gate and three exit gates which is divided into three Isle of parking lot where cars can park. An ant colony optimization algorithm (ACO) was developed as an effective management system for controlling navigation and vehicular traffic congestion problems when cars exit a motor park. The ACO based on the nature and movement of the natural ants, simulates the movement of cars out of the car park through their nearest choice exit. A car park simulation was also used for the mathematical computation of the pheromone. The system was implemented using SIMD because of its dual parallelization ability. The result showed about 95% increase on the number of vehicles that left the motor park in one second. A clear indication that pheromones are large determinants of the shortest route to take as cars followed the closest exit to them. Future researchers may consider monitoring a centralized tally system for cars coming into the park through a censored gate being.

A Distributed Ant Colony Optimization Applied in Edge Detection

With the rise of image data and increased complexity of tasks in edge detection, conventional artificial intelligence techniques have been severely impacted. To be able to solve even greater problems of the future, learning algorithms must maintain high speed and accuracy through economical means. Traditional edge detection approaches cannot detect edges in images in a timely manner due to memory and computational time constraints. In this work, a novel parallelized ant colony optimization technique in a distributed framework provided by the Hadoop/Map-Reduce infrastructure is proposed to improve the edge detection capabilities. Moreover, a filtering technique is applied to reduce the noisy background of images to achieve significant improvement in the accuracy of edge detection. Close examinations of the implementation of the proposed algorithm are discussed and demonstrated through experiments. Results reveal high classification accuracy and significant improvements in speedup, scaleup and sizeup compared to the standard algorithms.

用酶联免疫－化学发光法测定ANT的实验研究

本文报道了酶联免疫－化学发光法测定ＡＮＴ的实验研究．兔抗ＡＮＴ抗血清滴度１／５００～１／１０４，ＡＮＴ检测范围０～１０μｇ／ｍｌ．

添加Na^+对ANT系统介电性能的影响

Ag2O-Nb2O5-Ta2O5陶瓷系统(简称ANT)是一种新型的高频高介陶瓷材料,可以在1150℃以下进行中温烧结。在本系统中,添加Na+离子置换ANT系统中的A位A+离子形成ANNT系统,通过XRD,SEM以及能谱分析发现,少量Na+添加,导致晶格参数下降,即八面体空隙的体积将减小,从而抑制了Nb5+的松弛极化,有效地降低了ANT系统的损耗因子,使系统的介电性能达到:ε>500,tg δ≤5×10-4,容量温度系数αc=+12ppm/℃,ρv>1012Ωcm。

Antibacterial Effect of Waste Liquor of Essence Oil Extraction from Sabina vulgaris Ant in Foods

The antibacterial effects of waste liquor of essence oil extraction from Sabina vulgaris Ant on Escherichia coil, Staphylococcus aureus, Salmonella, Bacillus subtilis, Bacillus magaterium and Bacillus cereus in foods were evaluated by paper disk method. The results showed that the waste liquor of essence oil extraction from S. vulgaris had inhibitory effects on E. coil, S. aureus and Salmonella with bet- ter inhibitory effects on E. coil and Salmonella; the bacteriostatic effect of water steam distillation waste liquor was better than that of water extraction waste liquor. The more times the waste liquor was distilled, the higher the active ingredients content was, and the better the bacteriostatic effect was.

NT4p53(N15)Ant重组腺病毒对肝癌细胞腹腔种植瘤的治疗作用

目的研究NT4p53(N15)Ant融合基因重组腺病毒预先感染ICR小鼠腹腔后,对肝癌细胞株H22腹腔种植瘤的治疗作用。方法将16只ICR小鼠随机平均分成2组,分别于腹腔内预先感染Ad-NT4p53(N15)Ant(治疗组)及等量空病毒(对照组)。将H22细胞悬液接种于小鼠腹腔,建立小鼠腹腔泛发性种植瘤模型。根据小鼠生长情况、生存期以及腹水瘤细胞形态、细胞凋亡率和小鼠腹腔内瘤体重量等结果,评价Ad-NT4p53(N15)Ant对H22细胞种植瘤及癌性腹水的治疗效果。结果成功构建了小鼠腹腔泛发性种植瘤动物模型。与对照组相比,Ad-NT4p53(N15)Ant组小鼠生存期延长、腹水的产生时间延迟,腹水中多核巨细胞减少,细胞凋亡及坏死的比率升高,腹腔内瘤体的质量减少。结论 Ad-NT4p53(15)Ant可有效抑制H22肝癌细胞腹腔移植瘤生长,延迟腹水形成,诱导体内腹水瘤细胞凋亡及坏死,延长小鼠生存期。

NT4p53(N15)Ant融合基因重组腺病毒的构建及其体外抑瘤作用

背景与目的:有研究发现P53氨基端15肽与穿膜肽(antennapedia,Ant)的融合肽能迅速穿透细胞膜,直接、快速引起乳腺癌、胰腺癌细胞坏死而非凋亡,但对正常细胞几乎没有毒性。本研究构建缺陷型腺病毒载体表达NT4p53(N15)Ant融合基因,研究其体外抑瘤作用。方法:应用Ad-EasyTM系统,在大肠杆菌同源重组,构建NT4p53(N15)Ant腺病毒表达载体,在HEK-293细胞内成功包装并鉴定后,感染肝癌细胞株HepG2,用倒置相差显微镜、透射电镜观察细胞形态学变化、四甲基偶氮唑蓝(MTT)比色实验及培养基中的乳酸脱氢酶(lactatedehydrogenase,LDH)测定研究其体外抑瘤作用。结果:Ad-NT4p53(N15)Ant对肝癌细胞株HepG2有明显抑制作用,48、72、96h细胞存活率分别为36.67%、20.47%、17.82%,与空病毒处理组比较差异有统计学意义(P<0.05);电镜观察到感染的HepG2细胞胞膜、核膜破坏,胞浆内出现囊泡状物质,染色质聚集。Ad-NT4p53(N15)Ant处理HepG2细胞24、48、72、96h时培养液中LDH释放分别为94、236、267、313U/L,较空病毒处理组明显增加,其差异有统计学意义(P<0.05)。结论:构建的腺病毒载体Ad-NT4p53(N15)Ant感染HepG2细胞后能抑制细胞增殖。